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意大利家族性高胆固醇血症研究:一项叙述性综述。

The study of familial hypercholesterolemia in Italy: A narrative review.

作者信息

Bertolini Stefano, Pisciotta Livia, Fasano Tommaso, Rabacchi Claudio, Calandra Sebastiano

机构信息

Department of Internal Medicine, University of Genova, Genova, Italy.

Department of Internal Medicine, University of Genova, Genova, Italy.

出版信息

Atheroscler Suppl. 2017 Oct;29:1-10. doi: 10.1016/j.atherosclerosissup.2017.07.003.


DOI:10.1016/j.atherosclerosissup.2017.07.003
PMID:28965614
Abstract

In this review we outline our experience in the clinical and molecular diagnosis of familial hypercholesterolemia (FH), built up over more than three decades. We started our work by selecting FH patients on the basis of stringent clinical criteria, including extensive family studies. In most patients we confirmed the clinical diagnosis by showing a reduced LDLR activity in skin fibroblasts. After the isolation of LDLR cDNA and the characterization of the corresponding gene by the Dallas group, we started a systematic molecular investigation of our patients first using Southern blotting, and, subsequently Sanger sequencing. Up to now we have been able to identify 260 mutations of LDLR gene in more than 1000 genotyped FH patients, including 68 homozygotes. During this survey we identified 13 mutation clusters located in different geographical districts, which gave us the chance to compare the phenotype of patients carrying the most common mutations. We also found that mutations in APOB and PCSK9 genes were a rare cause of FH in our cohort. Despite our efforts, we failed to identify mutations in candidate genes in ∼20% of cases of definite FH. An exome-wide study, conducted within the context of an international collaboration, excluded the presence of other major genes in our unexplained FH cases. Recently, we have adopted sequencing technology of the next generation (NGS) with the parallel sequencing of a panel of FH targeted genes as a way of obtaining a more comprehensive picture of the gene variants potentially involved in the disease.

摘要

在本综述中,我们概述了三十多年来在家族性高胆固醇血症(FH)临床和分子诊断方面的经验。我们通过严格的临床标准(包括广泛的家族研究)来选择FH患者,以此开启我们的工作。在大多数患者中,我们通过检测皮肤成纤维细胞中低密度脂蛋白受体(LDLR)活性降低来确诊临床诊断。在达拉斯团队分离出LDLR cDNA并对相应基因进行特征描述后,我们首先使用Southern印迹法,随后使用桑格测序法对患者进行系统的分子研究。到目前为止,我们已经在1000多名基因分型的FH患者中鉴定出260个LDLR基因突变,其中包括68名纯合子。在这项调查中,我们确定了位于不同地理区域的13个突变簇,这使我们有机会比较携带最常见突变患者的表型。我们还发现,在我们的队列中,载脂蛋白B(APOB)和前蛋白转化酶枯草溶菌素9(PCSK9)基因的突变是FH的罕见病因。尽管我们做出了努力,但在约20%的确诊FH病例中,我们未能在候选基因中鉴定出突变。在一项国际合作背景下进行的全外显子组研究排除了我们无法解释的FH病例中存在其他主要基因的可能性。最近,我们采用了下一代测序技术(NGS),对一组FH靶向基因进行平行测序,以更全面地了解可能与该疾病相关的基因变异情况。

相似文献

[1]
The study of familial hypercholesterolemia in Italy: A narrative review.

Atheroscler Suppl. 2017-10

[2]
Spectrum of mutations in Italian patients with familial hypercholesterolemia: New results from the LIPIGEN study.

Atheroscler Suppl. 2017-10

[3]
Spectrum of mutations in index patients with familial hypercholesterolemia in Singapore: Single center study.

Atherosclerosis. 2017-12-27

[4]
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Atherosclerosis. 2016-12-18

[5]
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[6]
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[7]
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[8]
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[9]
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[10]
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引用本文的文献

[1]
Clinical exome-based panel testing for medically actionable secondary findings in a cohort of 383 Italian participants.

Front Genet. 2022-11-10

[2]
The Role of Registers in Increasing Knowledge and Improving Management of Children and Adolescents Affected by Familial Hypercholesterolemia: the LIPIGEN Pediatric Group.

Front Genet. 2022-6-20

[3]
Genetic spectrum of familial hypercholesterolemia and correlations with clinical expression: Implications for diagnosis improvement.

Clin Genet. 2021-11

[4]
Mutational Spectrum of and Genes Identified in Iranian Patients With Premature Coronary Artery Disease and Familial Hypercholesterolemia.

Front Genet. 2021-2-11

[5]
Molecular diagnosis methods in familial hypercholesterolemia.

Anatol J Cardiol. 2020-2

[6]
Human Dermal Fibroblast: A Promising Cellular Model to Study Biological Mechanisms of Major Depression and Antidepressant Drug Response.

Curr Neuropharmacol. 2020

[7]
Comparative assessment of different familial aggregation methods in the context of large and unstructured pedigrees.

Bioinformatics. 2019-1-1

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